بناء انموذج ديناميكي وانموذج هدفي في ظل البيئة الضبابية مع تطبيق عملي == Building of Dynamic Model And Goal Model Under Fuzzy Environment With Practical Application
Author name:
هبة الله سعد عبد الغني
Supervisor name:
محمد صادق عبد الرزاق الدوري
General topic:
Administration and Economics
Specific topic:
Operations Research
Degree:
Master
University:
University of Baghdad - Faculty Of Administration And Economics - Department Of Statistics
Language:
Arabic
University location:
Baghdad
First pages:
07T4139 - p.pdf
Abstract:
في مشكلة اقصر مسار لشبكة اعتيادية يفترض بان يكون صانع القرار متاكدا من البيانات في الشبكة, والتي تمثل الوقت والمسافة والكلفة...الخ, لكن في واقع الحياة توجد دائما شكوك حول هذه البيانات اي لايمكن تحديدها بشكل دقيق, ففي مثل هذه الحالة يتم تمثيلها بالاعداد | In the shortest path problem of classical network, It is supposed that the decision maker has assured from network data ,which represent time , distance and cost …etc. But in real live there are always suspicions about these data that is may not be determined exactly , in this case it is represented by fuzzy numbers.In this thesis a directed acyclic network was built with times represented by triangular fuzzy numbers to find to transport the medicines from Iscan store to Al_Amal hospital of cancer tumors where the shortest path has minimum time among other paths in the network ,two deferent methods were used for solving the problem, the first method is Bellman dynamic programming.In this method a fuzzy times are treated by signed distance ranking method and solve the problem as classical network. The second method is to formulate the problem with fuzzy times as a multi objective linear programming model and use the weighted additive method to unite the objective functions as a single objective function with a defined weights and then solve the problem classical linear programming we found the shortest path in both the methods are same and minimum time in the first method equal to the optimal solution for second method , and in addition minimum fuzzy time in the second method Is obtained.
